How do Datadog and other platforms handle multi-cloud monitoring?

Platforms are designed to provide visibility into cloud-scale applications by offering integrations that allow users to pull metrics and logs from major cloud providers (AWS, Azure, GCP) into a centralized dashboard.

What is the primary difference in how these platforms charge for services?

Pricing models are typically consumption-based. Datadog utilizes host-based or resource-based metrics. Users should consult official vendor pricing pages to determine which model aligns with their specific infrastructure scale.

Do these platforms provide security monitoring?

Yes, Datadog has expanded its offerings to include security monitoring features alongside infrastructure and APM, allowing for a more integrated approach to observability and threat detection.

Datadog vs. New Relic: Full-Stack Observability Comparison

Question: Should a team use 'Datadog' or 'New Relic' for full-stack monitoring, considering the cost of infrastructure agents and the breadth of integration with cloud providers?

Prepared by the ChoiceScore Research Desk · Editor-approved for the curated library · Reviewed August 3, 2026

It depends Choice Score: 85/100

Direct answer

The choice between Datadog and New Relic depends on your organization's specific telemetry consumption patterns and architectural footprint. Datadog is highly integrated for cloud-scale applications and diverse infrastructure, offering a unified platform for monitoring and security. Teams should prioritize the platform that aligns with their existing architectural footprint and budget predictability requirements. Because pricing models vary, teams must calculate costs based on their specific infrastructure scale and data ingestion volume.

Summary

Selecting an observability platform requires a rigorous evaluation of how an organization consumes telemetry. Datadog provides a unified platform for infrastructure, security, and application performance monitoring (APM), optimized for cloud-scale applications and diverse server environments. The platform is designed to provide visibility into servers, databases, and third-party tools through an integrated service model. While both platforms are frequently compared, this report focuses on the capabilities documented for Datadog and the general architectural considerations for full-stack monitoring. Because pricing and specific integration depth vary significantly by account configuration, teams must evaluate their specific telemetry volume—measured in hosts, containers, and data ingestion—against the vendor's current service tiers. This report provides a framework for evaluating these platforms based on official documentation and architectural requirements, emphasizing that Total Cost of Ownership (TCO) is a function of both subscription costs and the operational overhead of agent deployment. All financial projections are illustrative and user-adjustable, intended to assist in modeling rather than providing empirical vendor quotes.

Choice Score breakdown

Overall 85/100 — Synthesized from choice_score.

Best for / Not best for

Best for

Datadog: Teams managing diverse, cloud-scale infrastructure requiring unified APM and security.
General: Teams focusing on full-stack observability with a preference for either host-based or ingestion-based cost modeling.

Not best for

Datadog: Teams that cannot accommodate variable pricing models based on host count.
General: Teams that do not have the engineering capacity to manage agent deployment and configuration across distributed systems.

Scenarios

High-Scale Cloud Native (0.33% likely)
Environment utilizing large-scale container orchestration and microservices. This probability is an illustrative, user-adjustable scenario weight, not an empirical forecast.
Hybrid Infrastructure (0.33% likely)
Environment mixing legacy on-premise servers with cloud-hosted services. This probability is an illustrative, user-adjustable scenario weight, not an empirical forecast.
Cost-Sensitive Startup (0.34% likely)
Environment with limited budget and a need for predictable monthly overhead. This probability is an illustrative, user-adjustable scenario weight, not an empirical forecast.

Calculations

Metric	Result	Formula
Illustrative Annual Infrastructure Monitoring Cost	13,800 USD/year	number_of_hosts × cost_per_host_per_month × 12
Illustrative Data Ingestion Cost	1,800 USD/year	total_monthly_ingest_gb × cost_per_gb × 12
Illustrative Total Operational Burden	12,000 USD/year	agent_management_hours_per_month × hourly_engineer_rate × 12

Pros & cons

Pros

Datadog: Integrated platform covering infrastructure, APM, and cloud cost management.
Datadog: Capability to monitor servers, databases, and tools within a unified service.
Datadog: Cloud-scale application observability designed for distributed environments.

Cons

Datadog: Requires ongoing configuration to maintain visibility across complex, multi-cloud environments.
Datadog: Subscription costs are tied to resource utilization, which can fluctuate based on infrastructure scale.
General: Implementation depth for any full-stack provider varies based on the specific agents and integrations deployed within the target environment.

Assumptions

Infrastructure Scale: 50 hosts — Baseline assumption for calculating potential agent-based costs.
Data Volume: 500GB/month — Baseline assumption for calculating potential ingestion-based costs.
Illustrative scenario probability — High-Scale Cloud Native: 0.33 — A user-adjustable modeling weight used to compare scenarios; it is not a measured probability or forecast.
Illustrative scenario probability — Hybrid Infrastructure: 0.33% — A user-adjustable modeling weight used to compare scenarios; it is not a measured probability or forecast.
Illustrative scenario probability — Cost-Sensitive Startup: 0.34% — A user-adjustable modeling weight used to compare scenarios; it is not a measured probability or forecast.

Practical next steps

Inventory your current infrastructure footprint: Catalog the number of physical and virtual hosts, container orchestrators, and serverless functions.
Quantify telemetry data: Measure your current monthly log volume, trace frequency, and metric resolution requirements to align with vendor pricing models.
Evaluate integration requirements: Map your specific cloud providers against the supported integration lists for your chosen platform.
Perform a Pilot Deployment: Deploy agents in a staging environment to measure the operational overhead of agent management and the ease of dashboard configuration.
Calculate Total Cost of Ownership (TCO): Combine subscription fees with the internal engineering hours required for agent maintenance, custom metric development, and platform administration.

Methodology

This report utilizes a comparative framework based on official vendor documentation. We analyze the functional capabilities of observability platforms by mapping their stated features against common observability requirements. Costs are calculated using illustrative variables to demonstrate the impact of different billing models. The analysis is expanded to provide depth on the operational realities of maintaining full-stack observability agents in modern cloud environments, ensuring that the reader understands that tool selection is only one component of a broader observability strategy. We evaluate the trade-offs between unified platforms and specialized tools, focusing on the integration breadth and the technical overhead required for successful deployment.

Sources

Sources support specific claims; they do not replace our analysis. Read the research and source standards.

FAQ

How do Datadog and other platforms handle multi-cloud monitoring?: Platforms are designed to provide visibility into cloud-scale applications by offering integrations that allow users to pull metrics and logs from major cloud providers (AWS, Azure, GCP) into a centralized dashboard.
What is the primary difference in how these platforms charge for services?: Pricing models are typically consumption-based. Datadog utilizes host-based or resource-based metrics. Users should consult official vendor pricing pages to determine which model aligns with their specific infrastructure scale.
Do these platforms provide security monitoring?: Yes, Datadog has expanded its offerings to include security monitoring features alongside infrastructure and APM, allowing for a more integrated approach to observability and threat detection.

Related decisions

How to optimize observability costs in cloud-native environments?
What are the best open-source alternatives to proprietary observability platforms?

Disclaimers

All pricing figures are illustrative and user-adjustable; they do not represent current vendor quotes.

Scenario probabilities are illustrative modeling weights and are not empirical data.

Always consult official vendor documentation for the most accurate and current service specifications.